Identifying and tracking drinks bottles in OpenCV *without* machine learning

asked 2019-11-12 10:11:24 -0500

postlude gravatar image

updated 2019-11-12 11:51:53 -0500

Earlier this year Nick Bourdakos posted a series of tweets demoing drinks bottle detection and labelling using IBM's cloud annotation tool (built on top of Tensorflow)

I'd be interested in views from experts on this forum as to how close we could get to these results in OpenCV without machine learning.

I conducted a few initial experiments based on this tutorial and found that I could identify and label bottles pretty easily based or the label or bottle colour. However, I was unable to figure out how to extend the bounding box around the whole bottle rather than just the coloured region. I also considered using edge detection and identifying bottle or "not bottle" based on width / height ratio of the bottle's edge contour but due to the bottles being "hand held" it seems difficult to separate the hand to get a solid bottle edge.

If anyone has any thoughts on the best way to achieve this, or even if it is possible at all, I'd be interested to learn more.


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Can you tell me please, how is this off-topic?

postlude gravatar imagepostlude ( 2019-11-12 10:54:16 -0500 )edit

please make it relevant to opencv, a computer-vision and machine-learning library.

berak gravatar imageberak ( 2019-11-12 11:15:30 -0500 )edit